Laser radar characterization of atmospheric aerosols ...

Journal of Applied Remote Sensing, Vol. 4, 043503 (13 January 2010)

Laser radar characterization of atmospheric aerosols in the troposphere and stratosphere using range dependent lidar ratio Satyanarayana Malladi,a,b Radhakrishnan Soman Radha,a,c V. P. Mahadevan Pillai,a Veerabuthiran Sangipillai,b Presennakumar Bhargavan,b Murty Vinjanampaty,c and Reghunath Karnamd a

University of Kerala, Department of Optoelectronics, Kariavattom Campus, Trivandrum-695 581, Kerala, India [email protected] b Vikram Sarabhai Space Centre, Space Physics Laboratory, Trivandrum- 695 022, Kerala, India [email protected] c Indian Institute of Technology, Department of Physics, Madras, Chennai-600 036, India [email protected] d National Atmospheric Research Laboratory, Gadanki, Tirupati-517 502 , India [email protected]

Abstract. Laser radar (lidar) provides an excellent tool for characterizing the physical properties of atmospheric aerosols which play a very important role in modifying the radiative budget of the Earth’s atmosphere. One of the important issues in lidar research is to derive accurate backscattering or extinction coefficient profiles required for understanding the basic mechanisms in the formation of aerosols and identifying their sources and sinks. Most of the inversion methods used for deriving the aerosol coefficients assume a range independent value for the extinction-to- backscattering ratio [lidar ratio, (LR)]. However, it is known that in a realistic atmosphere the value of LR is range dependent and varies with the physical and chemical properties of the aerosols. In this paper, we use a variant of widely applied Klett’s method to obtain the range dependent LR values and derive the aerosol extinction profiles with good accuracy. We present the lidar derived aerosol extinction profiles in the upper troposphere and lower stratosphere corresponding to different seasons of the year of two distinctly different stations in the Indian subcontinent namely Trivandrum (8.330 N, 770 E), Kerala, India, a coastal station and Gadanki (13.50 N, 79.20 E), Tirupati, India an inland station. The range dependent LR is derived corresponding to different seasons of the year at the two stations. The lidar ratio, aerosol extinction coefficient (AEC), aerosol scattering ratio, and aerosol optical depth show strong to medium seasonal variation at both the stations. The optical properties of the aerosols at the two stations differ considerably as evident from the various parameters obtained. The lidar ratio values at Trivandum vary in the range of 1138 sr whereas the values range from 20-34 sr at Gadanki. AEC values at the Trivandum station vary from 7.9 x 10-6 to 6.9 x 10-5 m-1 and at Gadanki station the variation is from 1.27 x 10-5 to 6.9 x 10-5 m-1. It is proposed to use back-trajectory analysis to understand the sources of aerosol at the two stations. Keywords: remote sensing, lidar, atmosphere, aerosol, lidar ratio, extinction.

© 2010 Society of Photo-Optical Instrumentation Engineers [DOI: 10.1117/1.3306573] Received 8 Nov 2008; accepted 5 Jan 2010; published 13 Jan 2010 [CCC: 19313195/2010/$25.00] Journal of Applied Remote Sensing, Vol. 4, 043503 (2010) Downloaded from SPIE Digital Library on 26 Aug 2010 to 116.68.90.33. Terms of Use: http://spiedl.org/terms

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1 INTRODUCTION Particulate matter in the atmosphere, otherwise called aerosols greatly modify the solar radiation reaching the ground and also the long wavelength radiation emitted by the earth. The radiative effects of aerosols depend on the optical properties of the particulates in the Earth’s atmosphere. Aerosols are produced due to a wide variety of natural and anthropogenic sources. The role of the anthropogenic aerosols in the atmosphere is of great scientific interest due to the steady increase in the quantity of aerosols. Rapid industrialization and increase of automobile transport etc contribute for the production of atmospheric aerosols. Aerosols occur in different sizes in the range of 10-3 µm to 102 µm and get modified due to various physical and chemical processes in the atmospheric system [1]. The scattering and absorption characteristics of aerosols depend on their size parameter and refractive index. There are a number of experimental methods to characterise the physical and chemical properties of tropospheric and lower stratospheric aerosols [2], [3]. Lidar is one of the powerful techniques for characterizing the physical properties of aerosols [4], [5], [6]. It is well established that the lidar based aerosol measurements are useful in providing the vertical profiles of the aerosol properties with good spatial and temporal resolutions. Deriving the optical properties of aerosols from the experimentally obtained lidar data is one of the most interesting and challenging tasks for atmospheric scientists. Various methods had been developed so far, to obtain the quantitative profiles of extinction and backscattering coefficient from the pulsed backscattering lidar measurements. Among them, the Klett’s [7] and Fernald’s [8] methods are commonly used, even today, either directly or with some modifications for inverting the lidar signals to obtain the altitude profiles of the aerosol extinction coefficient [9]. Althausen et al [10] suggested another useful approach which requires the use of a highly sophisticated scanning six wavelength, eleven-channel aerosol lidar. Though this approach provides a breakthrough in the lidar inversion methods to retrieve the optical properties of aerosols unambiguously, the experimental system is relatively complex and measurements are needed at multiple wavelengths in addition to a Raman channel for nitrogen. Rajeev and Parameswaran [11] suggested the use of a threewavelength Nd: YAG lidar system and described an iterative approach which is a variant of the widely used Fernald’s backward integration method. The two-wavelength lidar inversion algorithm used by Ackerman [12], [13] based on the Klett’s and Fernald’s solutions requires the lidar data at two wavelengths and is applicable only to cases where the lidar ratio is in the range of 40 to 70 sr. The method can be applied to atmosphere with low aerosol concentration under certain experimental conditions. Kovalev [14], [15] presented a different iterative lidar inversion method, which is valid for the two component scattering atmosphere consisting of aerosols and gas molecules. In this method, the inversion procedure can be performed either with a constant or with a variable lidar ratio (aerosol extinction-to-backscattering ratio). Parameswaran et al [16], [17] studied the relationship between backscattering and extinction coefficient of aerosol, which is applicable for the limited case of turbid atmosphere. Kovalev and Eichinger [18] had summarized the different inversion methods, their limitations etc in great detail. A general solution for the lidar equation requires the value of the lidar ratio (LR) which is defined as the ratio of extinction and backscattering coefficient of aerosols applicable to different conditions of the atmosphere as a function of range [19], [20] . The LR depends on the size distribution, shape and chemical composition of the aerosols. These properties of aerosols are highly variable and mainly depend on their sources and the local meteorological parameters [19]. But such information is not easily obtained and one has to conduct complementary experiments to derive the same. In almost all the inversion methods, a typical range independent LR is assumed and used for different types of aerosols based on some previous data. Earlier studies by Kovalev [15] and Sassano [21], showed that an inaccurate LR value leads to large errors in the retrieval of aerosol extinction coefficient. In order to derive accurate aerosol extinction coefficient profiles at any site of observation, it is necessary to make use of true range dependent LR values. Studies are being conducted globally to measure the LR

Journal of Applied Remote Sensing, Vol. 4, 043503 (2010)

Downloaded from SPIE Digital Library on 26 Aug 2010 to 116.68.90.33. Terms of Use: http://spiedl.org/terms

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values corresponding to aerosols of different types like continental, marine, polluted atmosphere, dust, volcanic etc. But such measurements and the related LR data are confined to very limited locations globally. In the absence of direct LR data only an average value of the LR based on columnar measurement is used to derive the extinction coefficient profiles. As such the aerosol extinction profiles derived using a uniform LR value do not really represent the profiles with due consideration for the nature of the aerosols present at different altitudes. Hence, it is required to obtain the range dependent LR values for inverting the lidar data accurately. The present study makes use of a variant of the Klett’s backward integration method to derive the aerosol extinction profiles with good accuracy and resolutions using the range dependent LR derived from the lidar data itself. The range dependent proportionality constants (exponential and linear) relating to the LR are derived by using multiple iteration. The extinction coefficients profiles are derived using the LR values so obtained. Lidar observations are conducted at the two stations namely Trivandrum and Gadanki, India which represent the coastal and continental locations respectively. The derived LR profiles at the two stations show large variations with altitude. The seasonal variation of aerosol extinction coefficient corresponding to the coastal station, Trivandrum (8.330 N, 770 E), Kerala India and the inland rural station Gadanki (13.50 N, 79.20 E), Tirupati, Andhra Pradesh, India were studied and compared.

2 LIDAR SYSTEM DESCRIPTIONS A high-resolution monostatic multi-wavelength lidar (MWL) system was designed and developed in-house at the Space Physics Laboratory, Vikram Sarabhai Space Centre, ISRO and operational at the low latitude tropical coastal station, Trivandrum (8°33 N, 77°E), Kerala, India [22], [23], [24]. A Quantel (France) Model YG-581C-20- Nd: YAG laser, working in the second harmonic at 532 nm with a pulse width of 10 ns is the transmitting source of the lidar. The laser can be operated at pulse repetition frequency (PRF) of 10 Hz. The receiver consists of a 500 mm diameter Cassegrain-type telescope and the post optics assembly to provide a field of view (FOV) of 1 mrad. The photomultiplier tube (PMT) (EMI 9816B) assembly with S20 cathode having a narrow band interference filter of 0.5 nm band width is used along with the telescope. The backscattered signals collected by the telescope and detected by the PMT are digitised by the LICEL (Germany) 12-bit transient digitizer system capable of digitizing up to 40 mega samples per second. The dwell time of the counting system is 25 ns (bin width of 3.75 m). The backscattered returns are integrated for 300 seconds corresponding to 3000 laser shots and the lidar data acquired is stored in the computer hard disk for off-line analysis and quick look of the sample data. As a part of the major programme on atmospheric aerosols and clouds, the MWL system was installed at Trivandrum for carrying out studies on aerosols and clouds on a regular basis. The lidar system is in regular operation each night from 1900 to 2200 Indian Standard Time (IST) when the sky is relatively clear. Also in each month 8-10 days of over-night observations are being conducted. A pulsed monostatic lidar system was setup at the National Atmospheric Research Laboratory at Gadanki (13.5°N, 79.2°E), Tirupati, India in collaboration with Communication Research Laboratory, Japan, for the study of atmospheric aerosols and thermal structure of stratosphere and mesosphere [25], [26], [27]. The lidar uses an Nd:YAG laser (Powerlite 8020: Continuum) operating at its second harmonic of 532 nm with energy of 550 mJ, pulse width of 7 ns and PRF of 20 Hz. The receiver system employs a 350-mm-diameter Schmidt-Cassegrain-type telescope with a FOV of 1 mrad. PMT (Hamamastu R3234-01) with a narrow band interference filter centered at 532 nm (band width of 1.13 nm) is used after the polarization beam splitter which separates the beam into cross (S) and co (P) polarized components. The MCS-Plus (EG and G Ortec photo recorder) multi channel photon counter is used for recording the photon counting signals as a function of time (altitude). The dwell time of the counting system is 2 µs, which corresponds to an altitude resolution of 300 m. The backscattered returns summed for 250 seconds and are stored in a computer hard disk for off-line analysis. The lidar



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system is aligned to a height greater than 4 km so as to avoid the intense backscattered signals from the low altitude clouds and aerosols. The lidar system installed at the Gadanki station has been in regular operation since 1998. The lidar system is operated for about three hours in the pre-midnight period regularly, subject to sky condition and system integrity. In addition to this, the system is operated regularly every night from 2200 hrs to 0500 hrs IST. The lidar system operated at both stations near simultaneously and time averaged for about 2 hours. Lidar data from the Trivandrum station is smoothened by 80 point averaging (3.75m x80=300m) to compare it with the lidar signal at Gadanki where the data is obtained with vertical resolution of 300m. The standard deviation (1σ) of the measured signal at both the station is with in ±0.5 %.

3 KLETT’S LIDAR INVERSION METHODOLOGY WITH RANGE INDEPENDENT LIDAR RATIO 3.1 Single scattering Lidar equation By considering only single scattering condition, the backscattered signal power P(r) received from a pulsed lidar can be expressed as

P ( r ) = P0

⎧ r ⎫ cτ β ( r ) E 2 A exp ⎨− 2 ∫ α ( r ' ) dr ' ⎬ 2 r ⎩ o ⎭

(1)

Where , P0 is the transmitted laser power c is the speed of light, τ is the laser pulse width, E is the overall system efficiency, r is the range of the scattering volume from the lidar, A is the effective area of the receiving telescope, βt (r ) is the integrated volume backscatter function (expressed in m-1 sr-1) and

α t (r ) is the integrated volume extinction function (expressed in m-1 ) [2], [3]. Both α t (r ) and βt (r ) are the unknowns in the lidar equation. The contribution

of the

molecular atmosphere in backscatter and extinction functions are either assumed from a model or measured from other experiments. Subtracting the molecular contribution, the aerosol coefficients may be designated as β a (r ) and α a (r ) respectively. The relationship between the backscattering coefficient ( β a (r ) ) and extinction coefficient ( α a (r ) ) of aerosol in LR can be expressed in a slightly different form as, α ak ( r ) = S β

(r )

(2) Where, S is a range dependent parameter determined by the size and nature of aerosols, probing laser wavelength etc [17] and the exponent k is generally assumed to be a range independent constant. Eqn. 2 can be rewritten in logarithmic form as, a

k log α a ( r ) = log S + log β a ( r )

(3)

Based on the experimental findings by several authors, it is observed that the value of the exponent k may fall in the range of 0.8 to 1.2 depends on the nature of aerosols [28], [29], [30]. The parameter S varies widely between 10 and 100, depending mainly on the type of aerosols viz. dust, yellow sand, sea spray etc [31]. It should be emphasized that the extinction coefficient α a (r ) and the constants k and S in Eq.2 are not unique in the



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actual Earth’s atmospheric system but all the inversion methods try to converge towards their true values from the lidar measurements.

3.2 Klett’s lidar inversion solution with range independent lidar ratio The widely used Klett’s lidar inversion method using the range independent LR for the retrieval of aerosol extinction coefficient for the general atmosphere can be summarized briefly as under: When Xm(r) and X(r) are the lidar measured signals at the reference altitude and

successive range bins respectively, the Klett’s solution for the aerosol extinction coefficient at each altitude level r can be written as (assuming that k and S are independent of altitude),

α t (r ) =

⎧ −1 ⎨α t ⎩

⎛ X (r ) − X m ⎞ exp ⎜ ⎟ k ⎝ ⎠ 2 rm ⎡ ( X (r ) − X m ) ⎤ ⎫ + ∫ exp ⎢ ⎥⎦dr ⎬ k r k ⎣ ⎭

(4)

Where, αt (rm) is the total extinction coefficient at the reference altitude rm . rm corresponds to either the aerosol free altitude region (normally above 30 km) or the highest altitude of lidar measurements with sufficient signal-to-noise-ratio [7]. A modified Klett’s solution incorporating range dependant S value can be expressed as,

( s (r ) / sm k exp[( X (r ) − X m ) / k ] 1

α t (r ) =

1/ k ⎫⎪ ⎧⎪ 2 rm ⎛ s (r ) ⎞ −1 ⎜ ⎟ α exp[( X (r ) − X m ) / k ]dr ⎬ + ⎨ t ∫ ⎜ ⎟ k r ⎝ sm ⎠ ⎪⎭ ⎪⎩

(5)

Where, S (r ) is the range dependent parameter as in Eq. 2 and S m is the value at the reference altitude [32]. Eqn.5, as proposed by Klett is applicable for realistic atmosphere for deriving accurate extinction profiles. However, it could not be applied in practice as the range dependent S (r)values required for deriving range dependent LR values are not available easily from any of the existing methods. As such, the eqn. 4 is being widely used with range independent LR values.

3.2.1 Effect of the reference value of extinction coefficient on altitude profiles of aerosol extinction Most of the lidar inversion methods require a reference value of extinction coefficient αt (rm) to derive the altitude profiles of aerosol extinction coefficient as discussed above. The reference boundary value of extinction coefficient αt (rm) plays a significant role in the accuracy of the derived aerosol profiles from the lidar data as discussed by Knauss (1982) [33], Bissonatte (1986) [34] and Massao (1994) [35]. It may be mentioned that when the lidar data coverage extends beyond the aerosol free region, the solution for obtaining the extinction of aerosol will become straightforward. When the useful lidar data is available only up to an altitude below the aerosol free region, say 30-35 km above the ground, Eqn. 5 is to be used as described above. The absolute value of the aerosol extinction coefficient obtained from the lidar backscattered signal depends on the assumed value of LR [18], [36], [37]. As such the reference value αt (rm) and the range independent LR play significant role in the accuracy of the derived aerosol extinction profiles. To study the effect of reference boundary value of extinction coefficient, αt (rm) and an uniform LR on altitude profiles of aerosol extinction coefficient αa(r), we



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have used the actual lidar data obtained from the lidar experiments conducted using the multi-wavelength lidar system at the Space Physics Laboratory, Vikram Sarabhai Space Centre, Trivandrum, India. In this study, the reference boundary value αt (rm) , is taken using the aerosol model generated from various ground based experiments including a multi-wavelength solar radiometer for a period of three years at the Trivandrum station relating to the specific season of the year under various scientific programs [22], [23], [38]. It may be noted that αt (rm) represent the total extinction coefficient of the atmosphere given by:

αt (rm) =αa (rm) +αm(rm)

(6) Where, αa (rm) and αm(rm) are the aerosol and molecular extinction coefficient values at the reference altitude rm. A typical LR value of 20 sr (at the laser wavelength of 532 nm) corresponding to marine aerosols pertaining to the Trivandrum station is assumed in this study [28]. We adopted the Klett’s top to bottom backward integration method as described in section 3.2. The value of αt (rm) are varied up to ±20 % to study its effect on the lidar derived aerosol extinction coefficient αa (r) .

Fig.1. Variation in aerosol extinction coefficient

αa (r ) as a function of altitude

with different values of αt (rm) (a) α t (rm ) − 20% (b) α t (rm ) − 10% (c) α t (rm ) (d ) α t (rm ) + 10% (e) α t (rm ) + 20% .

Figure 1 shows the variation of aerosol extinction coefficient αa (r) as a function of altitude for different values of αt (rm) . The vertical line in the figure represents the reference value of the aerosol extinction coefficient, αa (r) , for different altitudes corresponding to the model profile. The percentage deviation of αa (r) for different altitudes with variation introduced in αt (rm) is measured from this vertical line. It can be seen from Fig. 1 that the error in the derived values of αa (r) was found to be significantly high (up to 15 %) above an altitude of 15 km and below this altitude the error is in the range of 2 to 5 %. It indicates the importance of αt (rm) in deriving the accurate aerosol profiles corresponding to the prevailing atmospheric conditions where the lidar data were taken.

3.2.2 Effect of variation of the assumed lidar ratio on aerosol extinction coefficient The effect of using a uniform (range independent) lidar ratio on the extinction coefficient profiles of aerosol was studied using the actual lidar data from the Trivandrum station.



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For deriving the aerosol extinction coefficient profile, a uniform LR of 20 sr (with k=1) as a typical value was used for this study and is shown as a vertical line in Fig. 2. αa (r) profiles are plotted for different values of LR viz., 10, 15, 25 and 30 as shown in figure.

Fig.2. Variation in aerosol extinction coefficient αa(r ) for different LR values. (a) LR=10 sr (b) LR=15 sr (c) LR=20 sr (d) LR=25 sr (e) LR=30 sr.

It can be seen that the variation of aerosol extinction coefficient with uniform LR is relatively high in the lower altitudes (up to 15 km). This clearly indicates that the nature and composition of aerosols in the lower altitudes are different from those of higher altitudes. At lower altitudes, the sources of the aerosols are more of local / regional origin and the particles are relatively large in size. Generally it is known that the lower tropospheric aerosols are a mix up of local/regional aerosols combined with those transported from far off regions due to atmospheric circulation, particularly during dust storm episodes [39], [40]. Thus, it is appropriate to select a range dependent LR to derive more accurate extinction profiles.

4 LIDAR INVERSION METHOD WITH RANGE DEPENDENT LIDAR RATIO USED IN THE PRESENT STUDY The real atmosphere at a location is always filled with particulate matter from different sources having different sizes, compositions etc. As such LR varies significantly along the lidar measurement path. In order to achieve the accurate inversion of the measured lidar signal to get the range resolved aerosol extinction profile, it is appropriate that the range dependent LR is to be used. In the present study we derive the range dependent LR from the lidar data by making use of a variant of Klett’s backward integration method. The range dependent proportionality constants k and S are obtained by repetitive iterations and the corresponding LR is used to derive the aerosol extinction profiles at the two lidar stations as described above. The various steps involved in the method to obtain the range dependent LR and the results on the seasonal variability of the extinction profiles at the two stations are presented in the following sections.

4.1 The Inversion Methodology The present lidar inversion method makes use of the Klett’s backward integration method described above with suitable modification to obtain the range dependent LR and the extinction coefficient profiles. To start with, the method requires a model aerosol extinction profile corresponding to the station and the experimentally measured lidar data. The ‘model aerosol profile’ (MP) is referred in section 3.2.1 is used in this study. The proportionality constants S and k of LR have values of 20 and 1 respectively. The LR value of 20 at the lidar wavelength of 532 nm corresponds to marine aerosols which are



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predominantly present at the coastal station Trivandrum is used [22], [24]. The measured lidar data obtained from the experiments using the lidar system described in section.2 is used to derive the aerosol extinction profile and is designated as the observed profile (OP). In obtaining the OP from the measured lidar data the same values of S and k are used as in deriving MP. The same reference altitude is selected in deriving both the profiles. Using the Eqn. 1, the ‘synthetic lidar signal’ is derived by combining the MP and the molecular extinction profile (RP) corresponding to this station. Molecular extinction values of this station at each altitude were calculated from the appropriate molecular density profiles by using the Rayleigh theory. The air density values are taken from the atmospheric neutral density model developed by Sasi and Sen [41] using the sounding rocket and balloon experiments. The calibration constant of the lidar system which depends on various lidar system parameters including the overall system efficiency etc is derived by comparing the synthetic lidar signal of MP and measured lidar signal of OP at a particular altitude level. This normalization is done at the highest altitude of lidar measurement to reduce the inaccuracies. The calibration constant is used to normalize the ‘synthetic lidar signal’ derived as above by comparing it with the measured lidar signal of OP. This is the usual normalization practice in generating the synthesised lidar data or comparing the lidar signals at the two different stations using two different lidar systems. Using this ‘synthetic lidar signal’ after normalization, the aerosol extinction coefficient profiles are calculated by iteratively modifying the k value with in the realistic range by keeping S as 20. The extinction coefficient having different k values are compared with OP to get the best fit of the two profiles. The realistic range of k values chosen in this iteration is based on various physical parameters of the atmosphere and those of aerosols of different origin as discussed by He et al [20]. The corresponding k value is identified as its true value for further analysis. In the next step, the atmospheric region of interest is segmented into different altitude bins of, say 5 km typically. The range bin can be selected based on the vertical resolution of the profile required for a particular study. Using the extinction coefficient profile derived from normalised ‘synthetic lidar signal’ with the true value of k derived as above, an ‘altitude integrated synthetic lidar signal’ profile is generated by putting different values of S at different altitude bins covering the total region. Both the RP values and the lidar calibration constant used for the generation of ‘synthetic lidar signal’ are taken for obtaining the ‘altitude integrated synthetic lidar signal’. By the repetitive iteration method, the optimum value of S corresponding to each altitude bin is obtained. The value of S so obtained for each altitude bin corresponds to the range dependent constant S which is a proportionality constant of LR. The integrated aerosol extinction profile with altitude dependent S and k is derived from the measured lidar signal using the Eqn. 5 as described in section 3.2 and then derived the corresponding LR values. We believe that the modified inversion method using the range dependent LR, which is derived from the measured lidar signal itself, gives a realistic extinction profile. 4.1.1 Measurement of range dependent lidar ratio and aerosol extinction profile: A Case Study The method is applied for deriving the range dependent S values and thereby the LR and extinction profiles using the data obtained from lidar measurements on December 17, 2006, a typical cloud free day at the Trivandrum station in the winter season. The various stages of the method are described below. The MP corresponding to the season is taken as described in section 3.2.1 and a ‘synthetic lidar signal’ is generated by putting k=1 and S = 20. Both the profiles from the measured lidar signal and the ‘synthetic lidar signal’ are plotted in Fig.3 and the corresponding aerosol extinction profiles are shown in Fig. 4.



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Fig.3. Variation of lidar signal strength with altitude Measured lidar signal on December 17, 2006 Synthetic lidar signal derived from MP with k=1 and S = 20.

Fig.4. Altitude Variation of aerosol extinction coefficient profile with k=1.0 and S = 20 of (a) MP and (b) OP.

From Fig.4, it can be seen that the difference in the two profiles are significantly large at the higher altitudes compared to the lower altitudes. Using the different values of k within the realistic range of 0.8-1.2, the extinction profiles are derived from the ‘synthetic lidar signal’ by repetitive iteration. These extinction profiles are compared with the OP which is derived from measured lidar signal are shown in Fig. 5 to achieve the best fit between them.



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Fig.5. Variation of aerosol extinction coefficient with altitude For different k values a) OP with S = 20 and k=1 (b) Derived from synthetic lidar signal with S = 20 and k=0.9 (c) Derived from synthetic lidar signal with S = 20 and k=1.0 (d) Derived from synthetic lidar signal with S = 20 and k=1.1 (e) Derived from synthetic lidar signal with S = 20 and k=1.2.

It is clear from Fig .5 that the extinction coefficient profile obtained with k value of 1.2 matches closely with the OP. This is shown more clearly in Fig. 6 by plotting the OP and the appropriate closely matched extinction profile with k =1.2.

Fig.6. Variation of aerosol extinction coefficient profile with altitude Derived from synthetic lidar signal with S =20 and k=1.2 (b) OP with S =20 and k=1.0.

It may be mentioned that the value of k so obtained is not unique but represents a value which gives the closest match between the two profiles. Further steps in the method make use of this value of k=1.2 which is believed to be the realistic or at least near realistic value of the aerosol system. From Fig. 6, it can be seen that two profiles are not matching fully throughout the altitude region. It is necessary to make them matched for the entire altitude region by putting different S values for different altitude bins in the selected synthetic extinction profile with k=1.2 as shown in Fig.6. By repeated iteration successively for the each range bin, the S values which provide the matching between the synthetic lidar signal and measured lidar signal profiles for different altitude range



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bins are obtained. The derived S values are 10, 12.5, 16.65 and 25 for the altitude bins of 25 -20 km, 20 - 15 km, 15 -10 km and 10 - 5 km respectively. The matched portions of the ‘altitude integrated synthetic lidar signal’ profiles are combined to get a profile for the whole altitude region and shown in Fig. 7.

Fig.7. Variation in lidar signal strength with altitude (a) Measured lidar signal profile (b) Altitude integrated lidar signal with different S values.

It can be seen from Fig. 7 that the simulated and measured signal profiles are almost identical in all the altitude regions. After obtaining the matched k value and the S values for each range bin, the aerosol extinction coefficient profile is calculated by using Eqn. 5 from the measured lidar signal and is shown in Fig. 8 (a). The aerosol backscattering coefficient profile, β a ( r ) is also derived from Eqn. 3 by using the appropriate k, S and

αa (r) values corresponding to each range bin. The LR values for different range bins are also calculated by taking the ratio of αa(r) and β a (r ) are shown in Fig. 8 (b). It may be mentioned that the LR values derived using the present method are realistic and well with in the range of data published by various authors earlier [19], [20].

Fig.8. (a) Aerosol extinction coefficient profile calculated using the range dependent LR derived from the method on December 17, 2006 and (b) the corresponding LR values.

It can be seen from above that the proposed inversion method can be effectively applied to invert the lidar data by deriving the aerosol extinction profile using the range dependent LR. The extinction profile derived takes in to consideration, the nature of aerosols existing at different altitudes at the time of observation.



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4.1.2 Sensitivity analysis of the selected model aerosol profile for initialization As mentioned in section. 4.1, the proposed method requires an initial reference extinction value of aerosol αa (rm) from a MP corresponding to the lidar observation site/region to initiate the iteration process. The sensitivity of the LR profile derived by this method to the possible error in the assumed aerosol extinction value αa (rm) from the MP is studied. The analysis is applied to the same data set shown in section 4.1 above. The reference extinction value is varied by ±5% and ±10% respectively from its true value. The k values obtained have a maximum deviation of ±1.05 % when the reference extinction value has an error of ±10%. It is also observed that the maximum deviation of LR is ±1.8 % in the altitude region of 14-16 km. Thus, it can be concluded that the proposed method uniquely gives the LR profile corresponding to the realistic atmosphere prevailing at the time of observation at the location/region even when the reference value has an error of ±10%. In section 3.2.2 it was observed that the errors in the extinction profile is quite high when a uniform LR is used and the use of an altitude dependent lidar ratio, obtained as above, provides a relatively accurate extinction profile.

4.3 Lidar experiments The lidar derived aerosol extinction profiles in the Upper troposphere (UT) and lower stratosphere (LS) corresponds to different seasons of the year of two distinctly different stations in the Indian subcontinent are studied, namely Trivandrum (8.330N, 770E), Kerala, India and Gadanki (13.50 N, 79.20 E), Tirupati, India. The lidar site located at Trivandrum, Kerala, India, is a tropical coastal station on the west-coast of Arabian Sea and away from the coast of about 500 m only. The terrain is fairly flat, sandy and mostly free of vegetation. Trivandrum being a coastal area has a dry weather during summer in March to May with maximum temperature reaching nearly 370. The months of June to September correspond to monsoon season with heavy rains and the period from November to February is the winter season with pleasant climate of temperature between 200 and 300 C. The lidar site at Gadanki, Tirupati, India which is approximately 390 m above the mean sea level (MSL) is located in an unpolluted continental rural site with the abundant vegetation. During summer season the convective activity is relatively high and the surface temperature generally ranges from about 220 C to 430 C during the period. In winter period the temperature varies from about 130 C to 320 C [42]. The station receives heavy rains during the months of August-September-October. The detailed description of the two lidar is given earlier in section 2.0. The lidar experiments at the two stations are conducted only during clear sky conditions every month in different seasons of the year. The lidar data sets are divided into different groups of months namely March-April-May (summer), June-July-August (summer monsoon) and December-January-February (winter) for the Trivandrum station. The corresponding months in Gadanki are March-April-May (pre monsoon), June-JulyAugust (summer) and November- December (post monsoon). The two stations under study are separated by a distance of about 700 km.

5 DATA ANALYSIS AND RESULTS The seasonal variation of the aerosol optical properties in the UT and LS of the two stations are studied. Lidar data corresponding to summer, summer monsoon and winter seasons of the year 2006 are analysed using the inversion method with range dependent LR as described in 4.1. The seasonal variation of the range dependent LR values, the aerosol extinction coefficient (AEC), the aerosol optical depth (AOD) and the aerosol scattering ratio (ASR) at the two stations are presented below [3], [18]. A comparative study of the parameters between two stations is also described.



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5.1. Aerosol optical properties at the Trivandrum station At Trivandrum (TVM) the LR, AEC, AOD and ASR values are found to exhibit seasonal variation in both LS and UT. For the sake of convenience, different altitude ranges are named as (i) 3-5 km: H1, (ii) 5-10 km: H2, (iii) 10-15 km: H3 and (iv) 15-20 km: H4. Fig. 9 shows the LR values for different seasons at the TVM station.

Fig.9. Seasonal variation of LR with altitude at TVM station (a) summer (b) summer monsoon and (c) winter, 2006.

In the summer season the LR values range from 35- 25 sr in H1, 24-17 sr in H2, 1615 sr in H3 and 15-14 sr in H4. In summer monsoon season LR values vary from 38- 35 sr in H1, 34-18 sr in H2, 18-16 sr in H3 and 15-11 sr in H4. In winter season the LR is found to be with in 25- 20 sr in the H2, 18-17 sr in H3 and 17-16 sr in H4. In all the three seasons of the year, the variation of LR is relatively low in the LS and in UT but the variation is high below the 9 km altitude in the troposphere. Summer LR values are higher compared to their values in winter in the region below 9 km. This may be due to mixing of clean-marine and clean continental aerosols at this coastal station as indicated by Parameswaran et al [43] in their study on the marine environment of Trivandrum using lidar. It can be seen that the LR values of the summer monsoon season are larger than those of other seasons through out the altitude region below 8 km and are in the range of 35-38 sr. This may be due to the transport of smaller particles in to UT resulting from strong convective activity in the summer monsoon season as reported by Parameswaran et al [43]. In the winter season the observed LR values are much lower indicating the presence of large particles as observed by Parameswaran et al [43]. The seasonal variation of the AEC at TVM station is shown in Fig. 10.

Fig.10. Seasonal variation of AEC with altitude at TVM station (a) summer (b) summer monsoon and (c) winter, 2006.



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In the summer season, the AEC values are in the range from 6.9 x 10-5 to 6.5 x 10-5 m-1 in H1, 6.5 x 10-5 to 5.06 x 10-5 m-1 in H2, 4.98 x 10-5 to 3.96 x 10-5 m-1 in H3 and 3.82 x 10-5 to 2.89 x 10-5 m-1 in H4. In the summer monsoon AEC values varies from 9.5 x 10-5 to 4.5 x 10-5 m-1 in H1, 4.07 x 10-5 to 2.44 x 10-5 m-1 in H2, 2.4 x 10-5 to 1.53 x 10-5 m-1 in H3 and 1.52 x 10-5 to 1.46 x 10-5 m-1 in H4 and in winter the corresponding values are 5.92 x 10-5 to 5.85 x 10-5 m-1 in H1, 5.8 x 10-5 to 2.84 x 10-5 m-1 in H2, 2.84 x 10-5 to 2.47 x 10-5 m-1 in H3 and 1.69 x 10-5 to 1.14 x 10-5 m-1 in H4. In summer the AEC values are higher in both UT and LS by an average of about 5-8 % compared to the other seasons. Summer monsoon AEC values are lower in UT compared to the other two seasons. In the winter season, the AEC are lower in the UT and above, and are higher in the LT than those of in summer monsoon period. The presence of the cirrus cloud in the altitude of about 15-16 km and also an aerosol layer at about 5-6 km can be seen in the AEC profiles with corresponding increased values. The high AEC values in the lower troposphere in this season may be due to the fine dust blown in to the site from far-off places. The observed aerosol layer at 5-6 km region is also due to the fine dust blown in to the Arabian Sea from deserts of west Asian countries. Large quantities of dust are raised into the atmosphere from the dust bowl of Arabian, Iran, Afghanistan, Pakistan and northwestern parts of India due to strong dust storm over southern part of central Asia. This is in consistent with the earlier studies conducted and explained by Veerabuthiran et al from authors’ laboratory [22], [24] using the back trajectory of air masses arriving at this station. The observed AOD values from the present study are 0.61, 0.45 and 0.4 in summer, summer monsoon and winter seasons respectively. The seasonal variation of ASR at the TVM station is shown in Fig. 11.

Fig.11. Seasonal variation of ASR with altitude at TVM station (a) summer (b) summer monsoon and (c) winter, 2006.

In summer season the ASR values are in the range of 2.9 to 2.5 in H1, 2.5-1.89 in H2, 1.79-1.5 in H3 and 1.1-1.01 in H4. In summer monsoon season they range from 2.47-1.68 in H1, 1.68-1.3 in H2, 1.26-1.1 in H3 and 1.1-1.01 in H4. In winter the values are ranges from 2.69-1.97 in H1, 2.53-2.1 in H2 and 1.8-1.4 in H3. In summer season ASR values are consistently higher in all the height ranges. In summer monsoon season, the ASR values are lower compared to the other two seasons. In winter season the presence of dust layers and cirrus clouds give rise to high values of ASR. From the above observations it is clear that the LR, AEC, AOD and ASR having their seasonal and altitude variation. The seasonal variation of LR with altitude shows very clearly that the properties of the aerosols are different at different altitudes implying that the LR values are range dependent. The source of the aerosols present at different altitudes might not be entirely from local region but could be mix of aerosols transported from other places.



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5.2 Aerosol optical properties in the Gadanki station The optical properties of aerosols at the Gadanki (GAD) station have been studied and are shown in Fig. 12, 13 and 14. Fig. 12 shows the LR values for different seasons at the GAD station.

Fig.12. Seasonal variation of LR with altitude at GAD station (a) summer (b) pre-monsoon and (c) post-monsoon, 2006.

In summer season it is observed that the LR values vary from 34- 32 sr in H2, 31-29 sr in H3 and 25-27 sr in H4. In the pre monsoon season LR values range from 27- 25 sr in H2, 25-23 sr in H3 and 23-20 sr in H4 while the post monsoon values are 28- 25 sr in H2, 24-22 sr in H3 and 21-20 sr in H4. Gadanki is an inland tropical station completely free of marine aerosols and the loading of smaller aerosol particles are relatively high in the UT and LS as reported in the earlier studies by Kulkarni et al [42]. The observed aerosols at this station are mainly from natural sources like vegetation and partly due to automobiles as the station is close to State High-way. The pre monsoon LR values are lower compared to those in the summer but higher compared to the post monsoon season. In the post monsoon season the LR values are relatively low as expected due to rainout. The seasonal variation of AEC at the GAD station in 2006 are shown in Fig. 13

Fig.13. Seasonal variation of AEC with altitude at GAD station (a) summer (b) pre-monsoon and (c) post-monsoon, 2006.

In summer season, the AEC values are vary from 8.1 x 10-5 to 6.9 x 10-5 m-1 in H2, 6.8 x 10-5 to 5.04 x 10-5 m-1 in H3 and 4.7 x 10-5 to 3.9 x 10-5 m-1 in H4. In pre monsoon the AEC values are in the range of 5.88 x 10-5 to 5.03 x 10-5 m-1 in H2, 4.9 x 10-5 to 3.22 x 10-5 m-1 in H3 and 3.2 x 10-5 to 1.42 x 10-5 m-1in H4. In post monsoon, the values vary from 1.7 x 10-5 to 1.27 x 10-5 m-1 in H2, 1.21 x 10-5 to 9.48 x 10-6 m-1 in H3 and 9.11 x 10-6 to 4.27 x 10-6 m-1 in H4. The values of AEC are higher in summer compared to the other two seasons. The pre monsoon values of AEC are higher than those of the post monsoon



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season. The observed data are in consistent with the early reported lidar measurements by Kulkarni et al [42]. The AOD values obtained by integrating the aerosol extinction coefficient over the entire column of lidar observation are not showing much seasonal variability and the corresponding values are 0.58, 0.5 and 0.52 in summer, pre monsoon and post-monsoon seasons respectively. The seasonal variation of the ASR at the GAD station is shown in Fig. 14

Fig.14. Seasonal variation of ASR with altitude at GAD station (a) summer (b) pre-monsoon and (c) post-monsoon, 2006.

In summer season the ASR values are in the range of 2.59 to 2.5 in H2, 2.7 to 2.28 in H3 and 2.26-1.85 in H4. In pre monsoon season it varies from 2.59 to 2.5 in H2, 2.39 to 2.27 in H3 and in H4 it ranges 2.3 to 2.1 and in post monsoon the values vary from 2.38 to 2.1 in H2, 2.36 to 2.08 in H3 and 2.08-1.89 in H4. The ASR values in the altitude region of 25-15 km in all the seasons appear to be generally same and have an increasing trend in the 15-9 km range. In the lower troposphere below 9 km the seasonal variation is more pronounced. Higher values of ASR are reported in this altitude region during 2001 and 2004 [42]. The values of ASR are lower in the post monsoon than those of pre monsoon season. Similar results are reported in summer season during 2001-2004 by Kulkarni et al [42]. The observed values of ASR are lower in the post monsoon period compared to the pre monsoon values. The AOD values at GAD are 0.58, 0.5 and 0.52 in summer, pre monsoon and post monsoon respectively. This indicates the overall aerosol loading in the atmosphere remains more or less same during all the seasons even though the seasonal effects are seen in some altitude regions. Such observations where reported by Kulkarni et al [42] through a comparative study conducted by them using lidar, MODIS and MST-Radar on the LS and UT aerosols. It may be mentioned that MP of Gadanki station was derived from various experiments conducted including lidar at the station over a period of five years during 2000-2004. The RP is derived by combining the lidar and MST-Radar measurements with radiosonde measurements [42].

5.3 Aerosol optical properties: a comparative study of the two stations It may be noted that the data at Trivandrum station are categorized under summer, summer monsoon and winter seasons whereas at Gadanki station the corresponding seasons are summer, pre monsoon and post monsoon respectively. In both cases the data are compared for the same set of month of 2006. The summary of the optical properties of aerosols as discussed above at the two stations is given in Table. 1.



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Table.1. Summary of the aerosol optical properties at Trivandrum (8.330 N, 770 E) and Gadanki (13.5°N, 79.2°E) and their seasonal variation.

LR-lidar ratio, AEC-aerosol extinction coefficient and AOD-aerosol optical depth.

6 CONCLUSIONS We present a modified Klett’s method to obtain the aerosol extinction profiles using the range dependent LR which is derived from the lidar data itself. The method requires a reference aerosol model profile, corresponding to the region, which was derived from ground based, balloon and rocket borne experiments. The method provides the k and S constants for different altitude segments needed for obtaining the corresponding LR. Using the LR profile, the aerosol extinction profiles are derived from the lidar data with good accuracy. The LR values obtained are well with in the range of values reported earlier by Takamura et al (1987&1994) [44], [45], Doherty et al (1999) [37], He et al (2006) [20] and Young et al (2007)) [19]. It is also observed that the effect of error in the assumed reference value of the aerosol extinction coefficient from the model profile, on the LR profile, is nearly insignificant. The method gives the realistic profiles of LR and AEC covering the upper troposphere and lower stratosphere. The seasonal variation of the aerosol properties are studied at the two stations namely Trivandrum (8.330 N, 770 E), Kerala, India and Gadanki (13.50 N, 79.20 E), Tirupati, India. The two stations are separated by a horizontal distance of about 700 km and correspond to different atmospheric conditions. Trivandrum is a costal station on the West coast of Arabian-sea whereas Gadanki is an inland station with rural environment. The nature and optical properties of aerosols are found to be different at the two stations and show seasonal variability. Further studies on the various parameters of the observed aerosols including their possible sources at the two stations are being pursuit.

References [1] [2]

J. Prospero, R. Chorlson, and B. Mohnen, "The atmospheric aerosol system: An overview," Rev. Geophys. 21, 1607-1629 (1983) [doi:10.1029/RG021i067p01607]. R. M. Measures, Laser Remote Sensing: Fundamentals and Applications," Wiley, New York (1984).



Page 17

[3] [4] [5] [6] [7] [8] [9] [10]

[11] [12] [13] [14] [15] [16]

[17] [18] [19]

[20] [21]

E. D. Hinkley, Laser Monitoring of the Atmosphere; Topics in Applied Physics, Springer, New York (1976). R. T. H Collis, "Lidar," Appl. Opt. 9, 1782-1788 (1970) [doi: 10.1364/AO.001782]. D. Cooper and W. E. Eichinger, "Structure of the atmosphere in an urban planetary boundary layer from lidar and radiosonde observations," J. Geophys Res. 99, 22937-22948 (1994) [doi:10.1029/94JD01944]. J. L. McElroy and T. B. Smith, "Lidar descriptions of mixed layer thickness characteristics in a complex terrain/coastal Environment," J. Appl. Meteorol. 30, 585-597 (1991) [doi: 10.1175/1520-0450]. J. D. Klett, "Stable analytical inversion solution for processing Lidar return signals," Appl. Opt. 20, 211-220 (1981) [doi: 10.1364/AO.20.000211]. F. D. Fernald, "Analysis of atmospheric lidar observations: some comments," Appl. Opt. 23, 652- 653 (1984) [doi: 10.1364/AO.23.000652]. C. Adolfo, F. Rocadenbosch, and M. Lopez, "Effect of noise on lidar data inversion with backward algorithm," Appl. Opt. 43, 2572-2577 (2004) [doi: 10.1364/AO43.002572]. D. Althausen, D. Muller, A. Ansmann, U. Wandinger, H. Hube, E. Clauder, and S. Zorner, "Scanning 6-wavelength 11-channel aerosol lidar," J. Atmos. Ocean. Tech., 1469-1482 (2000) [doi: 10.1175/1520-0426(2000)017 2.0.CO;2]. K. Rajeev and K. Parameswaran, "Iterative method for the inversion of multiwavelength lidar signal to determine aerosol size distribution," Appl. Opt. 37, 4690-4700 (1998) [doi: 10.1364/AO.37.004690]. J. Ackerman, "Two wavelength lidar inversion algorithm for a two component atmosphere," Appl. Opt. 36, 5134-5143 (1997) [doi: 10.1364/AO.36.005134]. J. Ackerman, "Two wavelength lidar inversion algorithm for a two-component atmosphere with variable extinction-to backscatter ratios," Appl. Opt. 37, 31643170(1998) [doi: 10.1364/AO.37.003164]. V. A. Kovalev, "Lidar measurement of the vertical aerosol extinction profiles with range-dependent backscatter–to-extinction ratios," Appl. Opt. 32, 60536065 (1993)[doi: 10.1364/AO.32.006053]. V. A. Kovalev, "Sensitivity of the lidar solution to errors of the aerosol backscatter to extinction ratio: influence of a monotonic change in the aerosol extinction," Appl. Opt. 34, 3457- 3462 (1995) [doi: 10.1364/AO.34.003457]. K. Parameswaran and K. O. Rose, "Spectral dependence of the relationship between backscattering and extinction coefficient in turbid atmosphere with application to lidar signal inversion," Ind. J. Rad. Space. Phy. 22, 166-179 (1993). K. Parameswaran, K. O. Rose, and B. V. Krishnamurthy, "Relationship between backscattering and extinction coefficients of aerosols with application to turbid atmosphere," Appl. Opt. 30, 3059-3071 (1991) [doi: 10.1364/AO30.003059] V. A. Kovalev and W. E. Eichinger, Elastic Lidar-Theory, Practice, and Analysis Methods, Wiley Interscience, NJ (2004) [doi: 10.1002/0471643173.biblio]. Y. M. Noh, Y. J. Kim, B. C. Choi, and T. Murayama, "Aerosol lidar ratio characteristics measured by multiwavelength Raman lidar system at Anmyeon Inland Korea," Atmos. Res. 86, 76-87 (2007) [doi:10.1016/j.atmosres.2007.03.006]. Q. S. He, C. C. Li, J. T. Mao, A. K. H. Lau, and P. R. Li, "A study on the aerosol extinction-to-backscatter ratio with combination of micro-pulse LIDAR and MODIS over Hong Kong," Atmos. Chem. Phys. 6, 3243-3256 (2006). Y. Sassano, E. V. Brovell, and S. Ismail, "Error caused by using a constant extinction/ backscattering ratio in the lidar solution," Appl. Opt. 24, 39293932(1985) [doi:10.1364/AO.24.003929].



Page 18

[22]

[23] [24]

[25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39]

[40]

M. Satyanarayana, S. Veerabuthiran, D. Ramakrishna Rao, and B. Presennakumar, "Coloured rain on the West Coastal region of India: Was it due to a dust storm?" Aer. Sci. Tech. 38, 24-26 (2004) [doi: 10.1080/02786820490247588]. M. Satyanarayana, D. Ramakrishna Rao, and S. V. Mohankumar," Multiwavelength laser radar studies in the atmosphere," Asian. J. Phys. 18, 191195 (2000). S. Veerabuthiran and M. Satyanarayana, "Lidar observations on atmospheric dust transported from south-west Asia to Indian West coast region: A case study of color rain event occurred during July 2001," Ind. J. Rad. Space. Phys. 32, 158-165 (2003). S. V. Sunilkumar, K. Parameswaran, and B. V. Krishnamurthy, "Lidar observations of Cirrus cloud near the tropical tropopause: General features," Atmos. Res. 66, 203-227 (2003) [doi: 10.1016/S0169-8095(02)00159-X]. Y. Bhavanikumar, C. Nageswara Raju, and M. Krishnaiah, "Indo –Japanese, lidar observations of the tropical middle atmosphere during 1998 and 1999," Adv. Atmos. Sci. 23, 711-725 (2006) [doi: 10.1007/s00376-006-0711-0]. V. Sivakumar, Y. Bhavanikumar, P. B. Rao, K. Mizutani, T. Aoki, M. Yasui, and T. Itabe, "Lidar observed characteristics of the tropical cirrus clouds," Radio Sci. 38(6), 1094 (2003) [doi:10.1029/2002RS002719]. R. W. Fenn, "Correlation between atmospheric backscattering and meteorological visual range," Appl. Opt. 4, 293-296 (1966) [doi: 10.1364/AO.5.000293]. N. Curcico and G. L. Knestrick, "Correlation between atmospheric transmission with Backscattering," J. Opt. Soc. Am. 48, 686-689 (1958) [doi:10.1364/JOSA.48.000686]. J. A. Fergusan and D. H. Stephens, "Algorithm for inverting lidar returns," Appl. Opt. 22, 3673-3675 (1983) [doi: 10.1364/AO.22.003673]. D. P. Donovan and A. I. Carswell, "Principal component analysis applied to Multiwavelength lidar aerosol backscatter and extinction measurements," Appl. Opt. 36, 9406-9424 (1997) [doi: 10.1364/AO.36.009406]. J. D. Klett, "Lidar inversion with variable backscatter/ extinction ratio," Appl. Opt. 24, 1638-1643 (1985) [doi: 10.1364/AO.24.001638]. D. C. Knauss, "Significance of the boundary value term in the Klett lidar inversion Formula," Appl. Opt. 21, 4194 (1982) [doi: 10.1364/AO.21.004194]. L. R. Bissonnette, "Sensitivity analysis of lidar inversion algorithm," Appl. Opt. 25, 2122-2125 (1986) [doi:10.1364/AO.25.002122]. M. Massao and T. Nobua, "Effect of misestimated far end boundary values on two common lidar inversion algorithm," Appl Opt. 20, 6451-6456 (1994) [doi: 10.1364/AO/.33.006451]. Y. Sassano and H. Nakane, "Significance of the extinction/backscatter ratio and the boundary value term in the solution for the two-component lidar equation," Appl. Opt. 23, 11-13 (1984) [doi: 10.1364/AO.23.0011_1]. S. Doherty, T. Anderson, and R. Charlson, "Measurement of the lidar ratio for atmospheric aerosols with a 1800 backscatter nephelometer," Appl. Opt. 38, 1823-1832 (1999) [doi: 10.1364/AO.38.001823]. K. Moorthy, "Multiwavelength solar radiometer network and features of aerosol spectral optical depth at Trivandrum," Ind. J. Rad. Space. Phy. 18, 194201(1989). A. Ansmann, D. Althausen, U. Wandinger,, K. Franke, D. Muller, F. Wagner, and J. Heitzenberg, "Vertical profiling of the Indian aerosol plume with sixwavelength lidar during INDOEX: A first case study," Geophys. Res. Lett. 27, 963-966(2000) [doi: 10.1029/1999GL010902]. Z. Liu, A. Omar, M. Vaughan, J. Hair, C. Kittaka, Y. Hu, K. Powell, C. Trepte, D. Winker, C. Hostetler, R. Ferrare, and Robert Pierce "CALIPSO lidar observations of the optical properties of Saharan dust: A case study of long range



Page 19

[41] [42]

[43] [44]

[45]

transport, Saharan dust over the western equatorial North Atlantic Ocean," J. Geophys. Res. 113, D7207 (2008) [doi:10.1029/2007JD008878]. M. N. Sasi and K. Sengupta, "A reference atmosphere for Indian Equatorial Zone from surface to 80 km," Scientific Report SPL: SR: 006:85, Space Physics Laboratory, Vikram Sarabhai Space Centre, Kerala, India (1985). P. Kulkarni, S. Ramachandran, Y. Bhavanikumar, D. Narayana Rao, and M. Krishnaiah, "Features of upper troposphere and lower stratosphere aerosols observed by lidar over Gadanki, a tropical Indian station," J. Geo. Phys. Res. 113, D17207 (2008) [doi:10.1029/2007JD009411]. K. Parameswaran, K. G. Vijayakumar, and B. V. Krishnamurthy, "Lidar observations on aerosol mixing height on a tropical coastal environment," Ind. J. Rad. Space. Phy. 26, 15-21 (1997). T.T akamura, Y. Sassao, and T. Hayasaka, "Ratio of aerosol backscatter to extinction coefficients as determined from angular scattering measurements for use in atmospheric lidar applications," Opt. Quant. Electron. 19, 293-302 (1987) [doi: 10.1007/BF02032687]. T. Takamura, Y. Sassao, and T. Hayasaka, "Tropospheric aerosol optical properties derived from lidar, sun photometer and optical particle counter measurements," Appl. Opt. 33, 7132-7140 (1994) [doi: 10.1364/AO.33.007132].



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